Functional Classification Models of Cities

After understanding what functional classification is, the natural question is:
How exactly do we classify cities based on their functions?

For this, urban geographers have given us various models and techniques—some focusing on one dominant function, others taking a multi-functional perspective.

Let’s explore two major models:

Dominant Functional Approach – Given by C.D. Harris

Let’s begin with the older and simpler model.

🔹 Who proposed it?

• C.D. Harris, a renowned urban geographer.

🔹 What does it suggest?

• Every city has one dominant function—that is, one activity where a majority of the working population is involved.
• Harris believed that this dominant function can be quantified.

He classified towns by analyzing:

1. Occupational Significance:
   → The function in which the largest number of people are employed.
2. Functional Importance:
   → Even if fewer people are employed, some functions are so vital that they define the town’s identity (e.g., a military town or religious centre).

🗂️ Harris’ Classification Categories:

He gave specific thresholds to categorize towns. For example:

Type of Town	Classification Basis
Manufacturing Town	>70% of employed population in manufacturing
Retail Centre	Majority in retail trade
Diversified City	At least 11% in transportation

⚠️ Limitations of the Harris Model:

While this model is straightforward, it has serious limitations:

• Most cities in the real world are multifunctional, not mono-functional.
• Using arbitrary cut-off points (like 70% or 11%) doesn’t reflect ground realities.
• It ignores the contribution of other functions that might be important but employ fewer people.

Hence, this model has limited utility in contemporary urban geography.

Multifunctional Approach – Given by Nelson

Let’s now look at a more sophisticated and realistic model.

🔹 Who proposed it?

• Nelson, using data from the U.S. Census.

🔹 What does it aim to do?

• Unlike Harris, Nelson believed that cities cannot be judged by just one dominant activity.
• So, he proposed a statistical method to understand the multifunctional nature of cities.

🔎 Methodology:

Here’s how Nelson went about it:

1. Identified 9 types of urban activities (based on the US census categories).
2. For each activity:
   • He calculated the average percentage of people employed.
   • Then, computed the standard deviation from that average.
3. Based on this, he determined how much a city’s employment pattern deviates from the national average.

🗂️ Nelson’s Classification:

Type of City	Criteria
Diversified Town	All 9 activities fall within the range of mean ± standard deviation → No dominant activity
Unifunctional Town	One activity lies above the positive standard deviation → Indicates dominance
Bifunctional Town	Two activities lie above the positive standard deviation
Highly Specialized Town	One activity is significantly above standard deviation; others very low

✅ Strengths of Nelson’s Model:

• Based on empirical and statistical data, not arbitrary thresholds.
• Recognizes the multi-functional nature of urban areas.
• Offers a realistic picture of urban function diversity.

Ashok Mitra’s Functional Classification of Indian Cities

🧑‍🏫 Who was Ashok Mitra?

• Ashok Mitra was a former Registrar General of the Census of India, and a pioneer in bringing Indian census data into academic geography.
• He attempted one of the most comprehensive functional classifications of Indian cities based on empirical data(from 1961 census)

🧮 His Methodology: Grouping Workers into Broad Functions

Ashok Mitra used Census industrial categories and grouped them into three broad functional categories:

Function Type	Census Industrial Categories	Description
A. Manufacturing	Categories III, IV, V, VI	Includes household industries, other industries, construction, and mining
B. Trade and Transport	Categories VII, VIII	Trade & commerce, and transport, storage & communication
C. Services	Category IX	Includes administration, education, health, finance, etc.

🧠 You might be wondering — what about Categories I and II? Well, those aren’t included here because they pertain to agricultural activities, and since this classification is focused on urban functions, such categories are deliberately excluded.

🏙️ Classification of Towns Based on Dominance

Using the above groupings, towns were classified into three types:

1. Manufacturing Town
   → If the total percentage of workers in Categories III–VI is greater than those in Categories VII+VIII or IX.
2. Trade and Transport Town
   → If percentage of workers in Categories VII+VIII is greater than either of the other two.
3. Service Town
   → If Category IX has the largest percentage of workers.

📐 Degree of Specialization: The Triangular Graph Method

Now comes the most unique part of Mitra’s classification — the triangular graph.

• He plotted each town as a point within an equilateral triangle, where each side represented 100% of one function type.
• Then he drew three concentric circles from the triangle’s centroid (where each function is 33.3%).

These circles represented increasing degrees of specialization:

Region in Triangle	Interpretation
Within 1st circle	Highly diversified town
Between 1st & 2nd circle	Moderately diversified
Between 2nd & 3rd circle	Specialized town
Outside the 3rd circle	Highly specialized town

This technique visually captures the balance or dominance among the three functions.

🧾 Findings of Ashok Mitra’s Study

Out of 2,528 towns:

• 736 were agricultural towns (i.e., workers in agriculture > any of the three groups)
• Out of 1,792 non-agricultural towns:
  • 655 = Manufacturing towns
  • 708 = Trade & Transport towns
  • 429 = Service towns

🏙️ Real-world Examples:

• Manufacturing Cities (high specialization):
  Ahmedabad, Surat, Jamshedpur, Ludhiana, Salem, Solapur
• Trade Cities:
  Moderately specialized and widely scattered across India
• Service Towns:
  Chandigarh, Gandhinagar, Bhubaneswar — mostly planned cities with an administrative character

✅ Key Contributions of Mitra’s Model

• First nationwide classification of Indian cities based on hard data.
• Introduced a visual method to capture functional diversity.
• Highlighted that the most common type of Indian city is the diversified city — one with no single dominant function, but multiple activities.

M.K. Jain’s Functional Classification (1991 Census-based)

🧑‍🏫 Who was M.K. Jain?

• An Indian geographer who, unlike others, emphasized that no single formula can classify towns universally.
• Proposed a flexible but quantitative approach, using the 1991 Census data.

🔍 Classification Criteria

M.K. Jain gave simple percentage-based thresholds to identify the functional nature of towns:

Town Type	Criterion
Monofunctional Town	If one activity employs ≥ 40% of the working population
Bifunctional Town	If no single activity ≥ 40%, but two sectors together ≥ 60%
Multifunctional Town	If more than two activities together ≥ 60%

🧠 Jain’s Key Insight:

• Cities cannot be classified based on a single rule or model.
• Different towns will have different mixes of economic functions depending on region, history, resource base, and planning.

So, instead of imposing rigid categories, Jain’s method gives a data-driven yet flexible framework to understand city functions.

Final Comparison of All Four Models

Model	Approach	Strength	Limitation
C.D. Harris	Dominant Function (Threshold-based)	Simple and direct	Ignores multifunctionality
Nelson	Statistical (Mean & SD)	Accurate & quantitative	Needs detailed occupational data
Ashok Mitra	Census-based + Triangular Graph	Visual + Indian context	More complex to compute
M.K. Jain	Percentage thresholds (flexible)	Adaptable, Indian census-based	Lacks graphical/spatial analysis